Nikita Chetverikovzedbyl.tech
Sovereign AI infrastructure · regulated organisations

Sovereign AI environments for organisations that cannot route sensitive work through public models.

A boutique practice that designs and deploys private AI infrastructure inside the client perimeter engineered for organisations operating under regulatory, contractual or data-residency constraints. Inference, retrieval and workflow remain under the client's control: auditable, vendor-independent, and aligned with the governance posture the organisation already operates under.

01 · What I do

Four engagement modes, scoped to where the organisation is in its sovereign AI adoption.

TIER 01

Assessment

A confidential workflow and infrastructure review. Output: a written architectural recommendation, sizing, isolation posture and a deployment roadmap. Delivered whether or not the engagement continues.

Review assessment scope
TIER 02

Deployment

Turn-key delivery of a sovereign AI environment inside the client perimeter inference, retrieval over the internal corpus, network isolation, and operator handover. Typical timeline: one to two weeks from kick-off to operational use.

Review deployment scope
TIER 03

Operations

Continuous lifecycle management under a defined SLA: model updates, corpus ingestion, monitoring, and governance reporting. A monthly review keeps the environment aligned with how the organisation actually uses it.

Review operations scope
TIER 04

Bespoke

Engagements that extend beyond the assistant internal document pipelines, line-of-business integrations, knowledge-graded interfaces. Fixed scope, fixed price, fixed timeline.

Review bespoke engagements
02 · Why a boutique practice

Why a boutique practice rather than a generalist consultancy.

01

Regulated-industry fluency

The practice operates exclusively with organisations under regulatory or contractual sensitivity legal, healthcare, finance, logistics, manufacturing. Questions around privilege, retention, jurisdiction, GDPR Article 28/32 and sector-specific governance are answered directly, without the translation tax of a generalist consultancy.

02

Fixed scope, fixed timeline

Engagements are scoped in writing before they begin. No open-ended hourly billing, no drift. If a requirement falls outside the agreed architecture, the practice surfaces it before the engagement starts.

03

Vendor independence by design

Every environment is built on an open-architecture stack, owned and operated inside the client perimeter. The client retains the ability to operate, modify or transfer the system without dependency on the practice, on a single model provider, or on an external inference platform.

04

Principal-led delivery

Engagements are led end-to-end by the principal, Nikita Chetverikov scoping, architecture, deployment, governance handover. No account layer, no junior delivery. Decisions reach the buyer in hours, not weeks.

03 · Productised entry

A pre-commissioned sovereign-AI appliance - Sanctum Box.

A pre-configured on-premise environment delivered with private inference and retrieval, sized to the engaging team. Specification, commissioning, and delivery handled under a single fixed fee.

  • Sized to the engaging team

    Three capacity bands aligned to team size: 2–5, 5–15, or 15+ users. Specification matched to workload at the point of order.

  • On-premise by architecture

    The appliance resides within client premises. No data leaves the perimeter at training, retrieval, or inference time.

  • Operations included

    Model lifecycle management, monitoring, and priority support included under a single engagement.

Best fit if

Sovereign AI is required quickly, without a separate architectural assessment. Team of 2–15+ users, with a defined budget envelope.

Requirements outside the standard configurations are addressed through the Architectural Assessment engagement above.

04 · Reference scenarios

Reference engagements across regulated environments.

REF 001
Law firm
PrivilegeNDA/MSA/DPASLANetwork isolation

Privileged document analysis under client-confidentiality constraints.

A twelve-attorney firm required AI-assisted analysis of NDAs, MSAs, DPAs, engagement letters, motions and discovery materials but could not route client-confidential text through a public model provider without breaching privilege. A sovereign inference environment was deployed inside the firm's perimeter, with retrieval over the document corpus and isolation at the network layer. Attorney-client privilege intact, response-time SLA honoured, drafting and review cycles materially compressed.

Read the full law-firm RAG case study
Users12
Time to deploy5 days
Per-contract review40m → 3m
REF 002
Private clinic
Medical recordsPatient intake interfaceICD-10On-premise

Structured medical records and patient intake without patient data leaving the clinic.

A private clinic required two capabilities: structured transcription of doctor–patient consultations into form-025/u records with ICD-10 coding, and a patient intake interface that captures symptoms and pre-visit context. Both run on infrastructure inside the clinic perimeter; no patient data leaves the building.

See the clinic NER deployment notes
Programs2
Record filling15m → 1m
Booking automation80%
REF 003
Research lab
DPIAGDPRFERPA-alignedAir-gap-capable

Sovereign AI capability for a research lab no student, grant or unpublished data leaving campus.

A university research group required ChatGPT-grade assistance over grant proposals, unpublished datasets and student records. Cloud assistants created a GDPR/FERPA exposure the DPO could not sign off. A sovereign inference environment was deployed inside the campus perimeter in fourteen days, with retrieval over the lab share, network isolation and DPIA-ready audit logging. Zero cloud calls leaving campus.

Read the 14-day research-lab rollout notes
Time to deploy14 days
Users~30 researchers
Cloud calls leaving campus0

Note -reference engagements are described with engagement-permissible detail. Quantitative outcomes vary per environment; figures shown are derived from comparable deployments and the practice's internal benchmarks. Engagement-specific scoping precedes any quantitative commitment. Discuss an engagement.

05Introductory call

An introductory conversation confidential, thirty minutes.

Describe the organisation, the workflows under consideration, and the constraints sensitive data cannot cross. The reply will be an honest assessment of whether sovereign AI is the appropriate response and, where it is not, a referral to a practice that is better suited.

Response< 24h, working days
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